Kohonen自己組織化特徴マップを用いた巡回セールスマン問題解法の改良

抄録

The Traveling Salesman Problem (TSP) is well known as one of the combinatorial optimization problem. In 1988, Angeniol et al. first applied Kohonen's Self Organizing feature Map (SOM) to the TSP. They demonstrated that the practical solutions (sub-optimal tour) were obtained by their proposed method in sufficiently short time compared with conventional methods;e.g. Hopfield Network, Simulated Annealing, Genetic Algorithm (GA) and Chaos Neural Network. In this paper, we have improved Angeniol's method to reduce the calculating time by the following modifications of (1) optimization of node creation timing and (2) adding a momentum effect for the update factor. Using the best combination of the several parameters in the modified method, we confirm that the modified method can be take just one fourth time compared with original method to solve the squarely located 36 cities TSP. Finally, we illustrate that the 200 cities TSP can be solved about one minute using our method on the personal computer.